NRT-DESE: Computational Materials Education and Training - Bridging Methods and Applications (COMET)

NRT-DESE：计算材料教育和培训 - 桥接方法和应用（COMET）

• 批准号: 1449785
• 负责人: Kristen Fichthorn
• 金额: $ 297万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-04-01 至 2021-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1449785&HistoricalAwards=false
• 关键词: NRT; DESE; Computational; Materials; Education

NRT-DESE: Computational Materials Education and Training - Bridging Methods and Applications (COMET)The discovery of new materials offers solutions to pressing technological problems facing our society. This National Science Foundation Research Traineeship (NRT) award prepares Ph.D. students at Pennsylvania State University with the skills to contribute to national efforts to discover and develop advanced materials with greater efficiency and lower cost. Density functional theory, a theory based in quantum mechanics that can accurately predict materials properties, is a core pillar of the effort. Addressing a need for density functional theory literacy across science and engineering, the program will bridge a gap between fundamental advances in density functional theory and its application for materials design. As capstone projects, trainees will learn to develop online teaching materials that will be available worldwide. Through internships with industry, interdisciplinary team projects, and international workshops, trainees will develop the combination of fundamental and applied research on a variety of tools that will promote collaborative innovation---across industry and academia, and across the globe. This program involves faculty from three colleges and six departments focused on interdisciplinary research on oxide interfaces, nanomaterials, organic electronics, and force-field development. The research and training will provide graduate students with a firm foundation in density functional theory based computational materials science in all its aspects, ranging from the development of density functional theory methods to its direct use to solve problems in materials science, to its integration into multi-scale modeling involving theory, empirical force-field development, and simulations. Additionally, this program will develop new coursework as well as a Computational Materials Science track within the Computational Science graduate minor and establish a professional development seminar series that will ultimately be available to all science and engineering graduate students.

计算材料教育和培训-桥梁方法和应用(彗星)新材料的发现为我们社会面临的紧迫技术问题提供了解决方案。这项国家科学基金会研究培训(NRT)奖为宾夕法尼亚州立大学的博士生培养技能，为国家以更高的效率和更低的成本发现和开发先进材料的努力做出贡献。密度泛函理论是这项工作的核心支柱，它是一种基于量子力学的理论，可以准确地预测材料的性质。针对科学和工程对密度泛函理论素养的需求，该计划将弥合密度泛函理论的基本进步与其在材料设计中的应用之间的差距。作为顶峰项目，学员将学习开发将在全球范围内使用的在线教学材料。通过行业实习、跨学科团队项目和国际研讨会，学员将发展对各种工具的基础研究和应用研究的结合，这些工具将促进跨行业、跨学术界和跨全球的协作创新。这项计划涉及来自三所学院和六个系的教师，他们专注于氧化物界面、纳米材料、有机电子学和力场发展的跨学科研究。该研究和培训将为研究生提供基于密度泛函理论的计算材料科学各方面的坚实基础，从密度泛函理论方法的发展到直接用于解决材料科学中的问题，再到将其集成到涉及理论、经验力场发展和模拟的多尺度建模中。此外，该计划将开发新的课程以及计算科学研究生辅修课程中的计算材料科学轨道，并建立一系列专业发展研讨会，最终将向所有科学和工程研究生开放。